Staff Software Engineer, ML Platform

Build Enterprise-Scale Infrastructure:

• Leverage infrastructure-as-code to manage complex cloud environments supporting critical ML and AI initiatives.
• Design Kubernetes-native systems, including controllers/operators where appropriate.
• Improve platform networking, security, and observability.

Sustain Platform Health and Performance:

• Own critical systems in production, including reliability, scalability, security, and cost efficiency.
• Identify and proactively address technical debt, operational risk, and platform bottlenecks.
• “Learn by doing” — Quickly ramp up to a complex tech stack (Terraform, Kubernetes, Istio, Crossplane, Go, TypeScript).

Enable Teams and Customers to Move Faster:

• Create abstractions and tooling that make it easier for teams and customers to deploy, run, and scale AI/ML workloads.
• Collaborate directly with customers to understand their ML infrastructure challenges and translate them into platform improvements.
• Balance speed and rigor—shipping quickly while maintaining a high bar for quality and safety.